Senior AI Engineer (LLM & Model Training)

Position Overview The AI Engineer will be responsible for designing, developing, training, and deploying advanced Artificial Intelligence and Machine Learning models to solve complex business and manufacturing challenges. This role requires deep hands-on experience in model training, fine-tuning Large Language Models (LLMs), and building scalable AI systems capable of operating in production environments. Working closely with Data Engineers, Software Engineers, Manufacturing, Quality, Supply Chain, and Digital Transformation teams, the AI Engineer will transform large-scale structured and unstructured data into impactful AI solutions that drive operational excellence, automation, and innovation across the organization. This position plays a critical role in enabling VinFast's vision of becoming a data-driven and AI-powered global EV manufacturer.

Key

Responsibilities AI Model Development & Training Design, develop, train, and optimize Machine Learning and Deep Learning models for production use cases. Fine-tune foundation models and Large Language Models (LLMs) for enterprise applications. Build AI solutions leveraging Computer Vision, Natural Language Processing (NLP), Generative AI, Predictive Analytics, and Recommendation Systems. Develop and execute model training pipelines, including data preprocessing, feature engineering, model validation, and performance evaluation. Conduct experiments to improve model accuracy, robustness, scalability, and inference efficiency. Apply transfer learning, reinforcement learning, and advanced deep learning techniques where appropriate. Generative AI & LLM Applications Develop and deploy Generative AI solutions using state-of-the-art foundation models. Build Retrieval-Augmented Generation (RAG) systems and AI Agents to support enterprise use cases. Optimize prompts, fine-tuning strategies, and inference workflows to improve model performance. Evaluate and benchmark various LLMs against business requirements and performance targets. Production Deployment & MLOps Deploy and maintain AI models in production environments. Implement model monitoring, performance tracking, retraining, and lifecycle management processes. Collaborate with Data Engineering teams to establish scalable data pipelines and feature stores. Utilize MLOps best practices for model versioning, deployment automation, and continuous improvement. Ensure AI solutions meet reliability, security, and governance requirements. Research & Innovation Stay current with emerging AI technologies, research, and industry best practices. Evaluate new algorithms, architectures, and tools that can create business value. Contribute to the long-term AI strategy and roadmap for VinFast. Support the adoption of AI across manufacturing, engineering, supply chain, customer experience, and corporate functions.

Requirements Required

Qualifications Bachelor's or Master's degree in Artificial Intelligence, Computer Science, Machine Learning, Data Science, Mathematics, Statistics, or a related field. Minimum 5 years of hands-on experience in AI, Machine Learning, or Deep Learning development. Proven experience training, fine-tuning, and deploying Machine Learning and Deep Learning models in production environments. Strong expertise in Python and modern AI/ML frameworks. Hands-on experience with: PyTorch TensorFlow Hugging Face Transformers Scikit-learn LangChain or equivalent frameworks Experience working with GPU-based training environments and model optimization techniques. Strong understanding of: Machine Learning Algorithms Deep Learning Architectures Transformer Models Computer Vision NLP Generative AI LLM Fine-tuning Experience with SQL and large-scale data processing. Strong analytical, problem-solving, and communication skills. Good command of English, both written and spoken.

Preferred

Qualifications Experience building and deploying enterprise Generative AI solutions. Hands-on experience with: RAG (Retrieval-Augmented Generation) AI Agents Multi-Agent Systems LLM Fine-tuning Prompt Engineering Experience with MLOps tools such as MLflow, Kubeflow, Airflow, Weights & Biases, or similar platforms. Familiarity with Docker, Kubernetes, and cloud platforms (Azure, AWS, or GCP). Experience developing Computer Vision models for defect detection, quality inspection, or industrial automation. Experience within Automotive, Manufacturing, Industrial AI, Robotics, or Smart Factory environments is highly preferred. Contributions to AI research, open-source projects, patents, publications, or Kaggle competitions are a plus.

Benefits Why Join VinFast Be part of a globally ambitious EV company transforming the future of mobility. Work on large-scale, real-world AI applications with tangible business impact. Access cutting-edge technologies, high-performance computing resources, and large enterprise datasets. Collaborate with world-class engineers, researchers, and technology leaders. Accelerate your career in an innovation-driven and fast-growing global organization. Key Requirement: Strong hands-on experience in training, fine-tuning, and optimizing Machine Learning, Deep Learning, and Large Language Models (LLMs) is essential. This role is intended for engineers who can build and deploy production-ready AI models rather than perform only data analysis or reporting activities.